Do Parents Meet Adolescents’ Monitoring Standards? Examination of the Impact on Teen Risk Disclosure and Behaviors if They Don’t

In this study, we examined how adolescents compare monitoring efforts by their parents to those of a "good parent" standard and assessed the impact of these comparisons on adolescent self-disclosure and risk behavior and their perceptions of their parents'' monitoring knowledge. Survey responses from 519 adolescents (12–17 years) at baseline of a larger, longitudinal study examining parental monitoring and adolescent risk were examined. Adolescents’ “good parent comparisons” differed greatly by monitoring areas (e.g., telephone use, health, money); however, between 5.5% and 25.8% of adolescents believed their parents needed to monitor their activities more than they currently were monitoring. Alternatively, between 8.5% and 23.8% of adolescents believed their parents needed to monitor their activities less often. These perceptions significantly distinguished adolescents in terms of their level of disclosure, perceived monitoring knowledge, and risk involvement. Adolescents who viewed their parents as needing to monitor more were less likely to disclose information to their parents (p<.001), less likely to perceive their parents as having greater monitoring knowledge (p<.001), and more likely to be involved in a risk behaviors (p<.001) than adolescents who perceived their parents needed no change. Adolescent disclosure to a parent is a powerful predictor of adolescent risk and poor health outcomes. These findings demonstrate that adolescents'' comparisons of their parents'' monitoring efforts can predict differences in adolescent disclosure and future risk. Obtaining adolescent "good parent" comparisons may successfully identify intervention opportunities with the adolescent and parent by noting the areas of need and direction of monitoring improvement.     

Local spin dynamics in magnetic molecular chains studied by NMR and μSR

We present NMR and μ⁺SR study of spin dynamics in one-dimensional and quasi-one-dimensional molecular magnets of recent synthesis. In particular, we focus on the so called Gd(hfac)₃NIT-R and CoPhOMe magnetic chains families. For Gd-R helimagnets we show some differences between “weakly frustrated systems” and “fully frustrated systems”. The different behaviour is due to the different radical inserted in the chains (R = Me, Ph for “weakly frustrated systems” and R = iPr, Et for “fully frustrated systems”). The existence of different phase transitions, particularly to 3D long-range magnetic order in Gd-Ph and to chiral order in Gd-iPr, is remarked together with a comparison between results obtained from macroscopic and microscopic investigating techniques. As regards CoPhOMe slowly relaxing chain, the ¹H NMR measurements confirm the freezing of the spins at low temperature, which prevents the 3D long-range order, and display the presence of two relaxation mechanisms related to distinct contributions to the local spin relaxation.     

Inhibitors of hepatitis C virus NS3.4A protease. Effect of P4 capping groups on inhibitory potency and pharmacokinetics

Reversible tetrapeptide-based compounds have been shown to effectively inhibit the hepatitis C virus NS3.4A protease. Inhibition of viral replicon RNA production in Huh-7 cells has also been demonstrated. We show herein that the inclusion of hydrogen bond donors on the P4 capping group of tetrapeptide-based inhibitors result in increased binding potency to the NS3.4A protease. The capping groups also impart significant effects on the pharmacokinetic profile of these inhibitors.     

Modeling <Emphasis Type="Italic">Neisseria meningitidis</Emphasis> metabolism: from genome to metabolic fluxes

Background  

Neisseria meningitidis is a human pathogen that can infect diverse sites within the human host. The major diseases caused by N. meningitidis are responsible for death and disability, especially in young infants. In general, most of the recent work on N. meningitidis focuses on potential antigens and their functions, immunogenicity, and pathogenicity mechanisms. Very little work has been carried out on Neisseria primary metabolism over the past 25 years.     

Simulation of human atherosclerotic femoral plaque tissue: the influence of plaque material model on numerical results

Background

Due to the limited number of experimental studies that mechanically characterise human atherosclerotic plaque tissue from the femoral arteries, a recent trend has emerged in current literature whereby one set of material data based on aortic plaque tissue is employed to numerically represent diseased femoral artery tissue. This study aims to generate novel vessel-appropriate material models for femoral plaque tissue and assess the influence of using material models based on experimental data generated from aortic plaque testing to represent diseased femoral arterial tissue.

Methods

Novel material models based on experimental data generated from testing of atherosclerotic femoral artery tissue are developed and a computational analysis of the revascularisation of a quarter model idealised diseased femoral artery from a 90% diameter stenosis to a 10% diameter stenosis is performed using these novel material models. The simulation is also performed using material models based on experimental data obtained from aortic plaque testing in order to examine the effect of employing vessel appropriate material models versus those currently employed in literature to represent femoral plaque tissue.

Results

Simulations that employ material models based on atherosclerotic aortic tissue exhibit much higher maximum principal stresses within the plaque than simulations that employ material models based on atherosclerotic femoral tissue. Specifically, employing a material model based on calcified aortic tissue, instead of one based on heavily calcified femoral tissue, to represent diseased femoral arterial vessels results in a 487 fold increase in maximum principal stress within the plaque at a depth of 0.8 mm from the lumen.

Conclusions

Large differences are induced on numerical results as a consequence of employing material models based on aortic plaque, in place of material models based on femoral plaque, to represent a diseased femoral vessel. Due to these large discrepancies, future studies should seek to employ vessel-appropriate material models to simulate the response of diseased femoral tissue in order to obtain the most accurate numerical results.

     

Review and classification of variability analysis techniques with clinical applications

Background

Representation of independent biophysical sources using Fourier analysis can be inefficient because the basis is sinusoidal and general. When complex fractionated atrial electrograms (CFAE) are acquired during atrial fibrillation (AF), the electrogram morphology depends on the mix of distinct nonsinusoidal generators. Identification of these generators using efficient methods of representation and comparison would be useful for targeting catheter ablation sites to prevent arrhythmia reinduction.

Method

A data-driven basis and transform is described which utilizes the ensemble average of signal segments to identify and distinguish CFAE morphologic components and frequencies. Calculation of the dominant frequency (DF) of actual CFAE, and identification of simulated independent generator frequencies and morphologies embedded in CFAE, is done using a total of 216 recordings from 10 paroxysmal and 10 persistent AF patients. The transform is tested versus Fourier analysis to detect spectral components in the presence of phase noise and interference. Correspondence is shown between ensemble basis vectors of highest power and corresponding synthetic drivers embedded in CFAE.

Results

The ensemble basis is orthogonal, and efficient for representation of CFAE components as compared with Fourier analysis (p ≤ 0.002). When three synthetic drivers with additive phase noise and interference were decomposed, the top three peaks in the ensemble power spectrum corresponded to the driver frequencies more closely as compared with top Fourier power spectrum peaks (p ≤ 0.005). The synthesized drivers with phase noise and interference were extractable from their corresponding ensemble basis with a mean error of less than 10%.

Conclusions

The new transform is able to efficiently identify CFAE features using DF calculation and by discerning morphologic differences. Unlike the Fourier transform method, it does not distort CFAE signals prior to analysis, and is relatively robust to jitter in periodic events. Thus the ensemble method can provide a useful alternative for quantitative characterization of CFAE during clinical study.     

Protein identification using MS/MS data

The subject of this tutorial is protein identification and characterisation by database searching of MS/MS Data. Peptide Mass Fingerprinting is excluded because it is covered in a separate tutorial. Practical aspects of database searching are emphasised, such as choice of sequence database, effect of mass tolerance, and how to identify post-translational modifications. The relationship between sensitivity and specificity is discussed, as is the challenge of using peptide match information to infer which proteins were present in the sample. Since these tutorials are introductory in nature, most references are to reviews, rather than primary research papers. Some familiarity with mass spectrometry and protein chemistry is assumed. There is an accompanying slide presentation, including speaker notes, and a collection of web-based, practical exercises, designed to reinforce key points. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP 6).